Internet Research最新文献

Purpose

Chatbots are vital for enhancing e-commerce sustainability by providing efficient customer support. Although previous studies have considered both linguistic and visual anthropomorphism as crucial factors in e-commerce chatbot design, their joint effects and their underlying mechanisms have not been thoroughly investigated. Drawing on insights from the literature on anthropomorphism and the elaboration likelihood model, this research attempts to examine the joint effects of the two types of anthropomorphism, the boundary condition, and the subsequent impact on purchase intention.

Design/methodology/approach

A research model was proposed and empirically tested using two laboratory-controlled experimental studies.

Findings

Linguistic anthropomorphism plays a dominant role over visual anthropomorphism in influencing social presence and communicative effectiveness. In addition, linguistic anthropomorphism harms persuasion through the mediating role of communicative effectiveness, and the fit between linguistic and visual anthropomorphism amplifies the negative effect on purchase intention. Moreover, shopping motivation serves as a boundary condition for the negative effect of anthropomorphism.

Practical implications

Chatbot designers should be cautious when using anthropomorphism in e-commerce chatbot design. The use of machine-like languages may be more persuasive than that of human-like languages, especially for utilitarian products. Notably, mismatched anthropomorphic elements may harm user experience.

Originality/value

This study enriches chatbot literature by examining the role of chatbot anthropomorphism in the e-commerce context. Moreover, this study provides a more comprehensive framework for understanding how chatbots’ linguistic and visual anthropomorphism jointly influence consumer behavior.

Purpose

The purpose of this study was to examine the effects of in-game situations (battle vs non-battle) and advertisement animation (static vs animated) on visual attention, memory, brand attitude and behavioral intention in eSports.

Design/methodology/approach

A 2 (advertisement animation: static vs animated) × 2 (in-game situations: non-battle vs battle) between-subject factorial design was developed. Participants wearing eye trackers watched a 2-min-and-30-s stimulus featuring manipulated variables. Subsequently, they completed a questionnaire designed to measure variables.

Findings

In-game situations significantly influenced visual attention, with non-battle contexts eliciting higher fixation duration and count. Moreover, fixation count positively affected both explicit and implicit memory. Additionally, implicit memory enhanced brand attitude, which in turn positively affected behavioral intention.

Practical implications

These findings guide eSports event organizers and brand managers in optimizing advertisement placement. Advertisements should be positioned in non-battle situations, where visual attention is higher. Repeated brand exposure is more effective than prolonged single exposures for enhancing memory retention and brand attitude. Lastly, unobtrusive advertisement exposure is essential because implicit memory plays a key role in shaping consumer attitudes and behavioral intentions.

Originality/value

This study advances eSports advertising research by identifying psychological mechanisms influencing consumer behavior. Moreover, the study extends the Limited Capacity Model of Motivated Mediated Message Processing (LC3MP) by demonstrating how cognitive resource allocation varies across in-game situations and advertisements. Furthermore, this research contributes to self-perception theory and the mere exposure effect by clarifying the distinct roles of explicit and implicit memory in shaping brand attitudes.

Purpose

This study examines how default bias, driven by the default positive review (DPR) rule – which automatically classifies reviews not provided by consumers within a specified period as positive – and rebate bias, associated with the conditional rebate strategy (CRS), where sellers offer rebates exclusively to consumers who submit positive reviews, distort the distribution of online product reviews over time and impact consumer satisfaction.

Design/methodology/approach

A key aspect of our method lies in developing latent variable models that capture the relationship between biased online reviews and consumer satisfaction levels. By applying our models to a panel dataset from Taobao – a leading Chinese e-commerce platform – and using insights from online consumer feedback surveys, we assess the extent of the biases introduced by DPR and CRS in a given feedback system. A hierarchical regression model was employed to investigate the impact of the proposed biases on consumer satisfaction.

Findings

Consumers who have previously written online reviews experience satisfaction outcomes 72.9% of the time with DPR and up to 81.3% when CRS is included. Implementing DPR may boost product sales to some extent, but it would significantly amplify consumer dissatisfaction, whereas offering a rebate could effectively alleviate consumer discontent, even though the rebate is conditional.

Originality/value

Our findings reveal the extent of biases introduced by CRS and DPR in online reviews and inform the consumer satisfaction debate regarding the phenomenon of excessive positive reviews resulting from these practices.

Purpose

Digital device recycling platforms (DDRPs) are customer-to-business online marketplaces that allow consumers to trade in or sell their used electronics, like smartphones and laptops, directly to a business for cash or credit. Guaranteed data destruction is a service provided by most DDRPs to securely erase all data on devices being recycled or traded in. Perceived credibility of the service refers to the extent to which customers are confident in the effectiveness and reliability of the service offered by a given DDRP. Grounded in privacy calculus theory, the current study aims to explore the influence of perceived credibility of guaranteed data destruction service (GDDS) on one’s intention to use a DDRP.

Design/methodology/approach

An empirical study was conducted through an online survey of Chinese DDRP users. The proposed model was tested by analyzing the collected data using the structural equation modeling approach.

Findings

Our results indicate that perceived credibility of GDDS affects users’ intention to use DDRPs by decreasing privacy concerns and increasing perceived convenience and environmental benefits of these platforms.

Research limitations/implications

This study’s findings are based on data collected from Chinese DDRP users, which may limit the generalizability of the results to other cultural or market contexts.

Practical implications

This study provides practical guidance for DDRPs, emphasizing the importance of enhancing perceived credibility through transparent data destruction practices and certifications.

Originality/value

The findings of the current study offer implications for theory development in sustainable information technology and e-commerce as well as practical suggestions for increasing usage of DDRPs.

Purpose

This study aims to explore and understand the literature on digital transformation (DT) research that will lead to developing a conceptual and thematic structure of DT management.

Design/methodology/approach

The research approach employed a hybrid approach of bibliometric analysis and a structured review of DT management research studies from 2017 to 2023. Although systematic reviews and bibliometric analysis are distinct methods, they complement one another in research by enabling the synthesis and analysis of existing literature. Scopus and Web of Science (WoS) were selected as the bibliographic databases for this study since they are generally accepted as the most comprehensive data sources for various purposes.

Findings

Findings revealed 186 publications during these periods, with the top three publications being the Journal of Business Research, Business Horizons and California Business Review. Top-ranking researchers hailed from Germany, Japan and Spain. Keywords that appeared were innovation, digital transformation, artificial intelligence and DT. In the management area, there are fewer studies conceptualising DT management that led to this study forming a conceptual framework using a qualitative, interpretative and thematic analysis approach.

Originality/value

These findings are relevant for understanding the phenomenon of DT and DT management. The study contributes to the emerging body of knowledge in management and DT.

Purpose

In the current digital transformation era, guiding employees toward realizing self-leadership has become a critical strategy for enterprises to mitigate the risks of external uncertainty. This study explores the intrinsic relationship between enterprise social media (ESM) communication visibility and self-leadership on the basis of communication visibility theory (CVT) and conservation of resources theory (COR) to support the sustainable growth of employee self-leadership.

Design/methodology/approach

Data were collected from 332 Chinese employees across three stages. Hierarchical regression analysis and the bootstrap method were employed to test the hypotheses.

Findings

Network translucence and message transparency positively affect self-leadership. Relational energy and job control mediate the relationship between communication visibility and self-leadership. Moreover, response expectations weaken the positive relationship between relational energy and self-leadership as well as between job control and self-leadership.

Practical implications

Managers can use ESM to provide work and social support for employees’ job control and social network development to achieve long-term maintenance of employees’ self-leadership. At the same time, within the context of ESM use, moderately reducing response expectations can offer situational support for employees to achieve self-leadership.

Originality/value

This research sheds light on the internal mechanism by which ESM communication visibility affects self-leadership and explores the key boundary conditions that impact how self-leadership is formed. These findings expand the understanding of self-leadership development in the context of ESM use and offer new technical insights for guiding and fostering sustainable employee self-leadership.

Purpose

Users contribute to online communities by posting and responding to discussion threads. Nonetheless, only a small fraction of threads gain popularity and shape community discourse. Prior studies have identified several factors driving thread popularity; however, despite their prevalence, the role of emotional expressions within discussion threads remains understudied. This study addresses this gap by investigating the impact of thread starters’ valence and embedded discrete emotions of anger, anxiety and sadness on thread popularity, drawing on the negativity bias and the emotion-as-social-information theories.

Design/methodology/approach

Using two samples from Reddit, this study employs negative binomial regression analysis to examine the hypothesized relationships.

Findings

The results demonstrate that negativity in thread starters significantly influences thread popularity; however, the expression of discrete emotions impacts popularity variously. In some contexts, such as COVID-19 vaccination subreddits, embedded anger in thread starters decreases thread popularity, whereas anxiety and sad expressions enhance it. In other contexts, such as professional discussions (e.g. r/Medicine subreddit), anger and anxiety expressions increase thread popularity, while sad expressions have no significant influence.

Research limitations/implications

The study is limited by its focus on specific emotions and contexts. Future research could examine a broader range of emotions, post-content modalities and the impact of cultural and linguistic differences.

Originality/value

This study contributes to theory by offering a new definition of thread popularity and enhancing our understanding of the impact of emotions in online discussions. It also provides practical implications for online community members and moderators seeking to promote discussion posts that help achieve community goals.

Purpose

This study explores how employees respond to social media-induced fear of missing out (FoMO) in the workplace and examines the subsequent impacts of these responses. Based on the transactional theory of stress and coping, the research focuses on how FoMO affects employees’ adoption of stress-coping behaviors: active work interruption (a problem-oriented strategy) and social network interaction (an emotion-oriented strategy). It further investigates the outcomes of these coping strategies – job burnout (resulting from the problem-oriented strategy) and workplace relationships (resulting from the emotion-oriented strategy). Additionally, the study explores how the perceived competitive climate moderates the effect of FoMO on these coping behaviors.

Design/methodology/approach

A two-phase survey yielded 244 responses, which were then analyzed using covariance-based structural equation modeling to validate the relationships among the variables.

Findings

The findings revealed that FoMO increases employees’ active work interruption, leading to job burnout. In addition, FoMO leads employees to engage in more social network interaction, which promotes workplace relations. The perceived competitive climate positively moderates the indirect effect of workplace FoMO through active work interruption and job burnout.

Originality/value

This study emphasizes that individuals are not merely passive recipients of stress but active agents in coping with it. This shift from “passive impacts” to “active responses” helps uncover the bidirectional impacts of social media-induced FoMO on employees, thereby enriching our understanding of FoMO and expanding the application of the transactional theory of stress and coping. Additionally, we explore the boundary conditions of the FoMO mechanism and advance research related to the perceived competitive climate.

Purpose

This study investigates the effect of de-influencing and its related content on consumer behavior compared with influencing content. It considers the gender of de-influencers and consumers’ varied reactions to distinct types of de-influencing.

Design/methodology/approach

Based on informational social influence theory, we conducted three experiments to investigate how consumers perceive and respond to de-influencing: the first explores consumer perception of social media de-influencers compared to influencers; the second examines the effect of de-influencers’ gender and the last compares consumer attitude toward various types of de-influencer content.

Findings

Consumers find de-influencers more credible than “traditional” influencers. De-influencing messages significantly affect attitude and purchase intention. The de-influencing creator’s gender does not affect brand attitude, perceived message effectiveness or perception. However, de-influencing video content influences attitudes toward brands and video effectiveness. Messages focusing on ethics and health elicit more negative perceived attitudes toward the brand.

Research limitations/implications

This pioneering research introduces “de-influence” as a new dynamic in social media marketing, revealing consumers’ preference for authentic, skeptical content over traditional influencer promotions. This lays the foundation for future research on consumer behavior and brand perception in digital spaces.

Practical implications

Brands in trust-sensitive industries should embrace authenticity and engage with de-influencers to build trust, turn criticism into growth opportunities and align themselves with consumer value.

Originality/value

Our study represents pioneering research in the emerging field of de-influencing, filling gaps in the literature and offering a comprehensive contribution to social media research.

Purpose

The persistence and virality of conspiracy theories online have raised significant concerns. This study revisits Rogers’ Diffusion of Innovations theory to examine the spread of conspiracy theories on social media, specifically focusing on how factors influencing their diffusion evolve over time.

Design/methodology/approach

The study analyzes over 1.18 million COVID-19-related tweets using a combination of natural language processing, social network analysis and machine learning techniques. It explores the dynamic roles of novelty, content negativity, influencers, echo chamber members and social bots in the diffusion of conspiracy theories.

Findings

The results indicate that novelty, influencers, echo chamber members and social bots are positively associated with the spread of conspiracy theories. The initial dissemination of conspiracy theories is primarily driven by content novelty and influencer involvement. Over time, the perpetuation of these theories becomes increasingly influenced by content negativity and the involvement of echo chamber members and social bots. Social bots serve as important connectors within echo chambers and their removal significantly reduces network cohesion.

Practical implications

The findings provide practical guidance for social media platforms and policymakers in monitoring diffusion patterns and applying targeted interventions.

Originality/value

This study introduces a time-sensitive approach to understanding the spread of conspiracy theories on social media. By identifying the key drivers at different stages of the diffusion process, this study offers valuable insights for developing effective strategies to counteract the proliferation of conspiracy theories at various points in their lifecycle.